Evidence map›Paper›PMID 42310757›Full record

ArticlePopulation health metrics2026

Trends and geographic differences in life expectancy in Australia during the COVID-19 pandemic: a multiple cause of death analysis.

Tim Adair, Sergey Timonin, Vladimir Canudas-Romo

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Article in Population health metrics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Tim AdairThe Nossal Institute for Global Health, Melbourne School of Population and Global Health, The University of Melbourne, Level 2, 32 Lincoln Square North, Carlton, 3010, VIC, Australia. timothy.adair@unimelb.edu.au.
Sergey TimoninCentre of Epidemiology for Policy and Practice, National Centre for Epidemiology and Population Health, College of Law, Governance and Policy, The Australian National University, Canberra, Australia.
Vladimir Canudas-RomoSchool of Demography, Research School of Social Sciences, College of Arts and Social Sciences, The Australian National University, Canberra, Australia.

Funding

Australian Research Council DP210100401Australian Research Council FT240100506
6 · The paper itself

Abstract

backgroundDuring the pandemic, Australia experienced relatively stringent restrictions and a distinctive life expectancy trend.This study assesses the contribution of multiple causes of death to these trends, as well as geographic differences in life expectancy, during the pandemic across Australia.

methodsData on deaths by age, sex, cause and capital city classification in Australian death registration data from 2017 to 2023 were accessed from the Australian Bureau of Statistics. We estimated life expectancy at birth and applied decomposition techniques to quantify the contribution of multiple causes of death to changes in life expectancy, including by capital city. Multiple cause of death analysis measured whether a death involved respiratory infections and/or COVID-19, and the accompanying underlying cause of death.

resultsOver half the 0.6 years life expectancy increase from 2017-19 to 2020 was from fewer deaths involving respiratory infections such as pneumonia, especially at age 80 years and above. Following a small life expectancy decline from 2020 to 2021, most of the 0.7 years decline in life expectancy in from 2021 to 2022 resulted from large increases in COVID-19 mortality following relaxation of restrictions. Deaths with a respiratory infection but not involving COVID-19 mostly had a non-communicable disease such as cardiovascular disease as the underlying cause. All geographic regions mirrored national trends by experiencing life expectancy increases in 2020 (especially from lower respiratory infection mortality) and declines in 2022 due to rising COVID-19 deaths, with the worst trends in Melbourne.

conclusionsAustralia experienced large fluctuations in life expectancy during the COVID-19 pandemic that were unique compared with many other high-income countries. The life expectancy increase in 2020 was mostly due to reduced circulation of respiratory infections like pneumonia during restrictions. However, upon cessation of restrictions in 2022, a large increase in COVID-19 mortality led to substantial life expectancy falls. Life expectancy trends did not vary greatly by capital city because restrictions were effective at preventing further deaths from COVID-19 after local outbreaks. Multiple cause of death data are very useful to understand the interaction of COVID-19, respiratory infections and non-communicable diseases during pandemic and the role of pandemic-related restrictions.

Indexed as

COVID-19Life ExpectancyAdolescentAdultAgedAged, 80 and overAustraliaCause of DeathChildChild, PreschoolFemaleHumansInfantInfant, NewbornMaleMiddle AgedAustraliaCOVID-19Geographic differences.Life expectancyMortalityMultiple causes of death

Identifiers

PMID42310757
PMCPMC13520252

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.